Modern inventory systems, such as those in mail order warehouses, supply chain distribution centers, airport luggage systems, and custom-order manufacturing facilities, face significant challenges in responding to requests for inventory items. As inventory systems grow, the challenges of simultaneously completing a large number of packing, storing, and other inventory-related actions become non-trivial. In inventory systems tasked with responding to large numbers of diverse inventory requests, inefficient utilization of system resources, including space, equipment, and manpower, can result in lower throughput, unacceptably long response times, an ever-increasing backlog of unfinished actions, and, in general, poor system performance.
To mitigate such challenges, many existing inventory systems have been automated. The automation generally involves a fleet of mobile robots. Each of the mobile robots moves around an inventory space and supports, within the space, a set of inventory-related actions specific to a set of items. The use of mobile robots has improved the efficiency and flexibility while also driving down the overall operational cost of inventory systems.
However, the automation for oversize, overweight, or uniquely shaped items remains a challenge. An existing approach involves developing and deploying relatively larger and/or specialized mobile robots specifically designed to handle such items. This approach incurs a high developmental and operational costs and can result in a loss of efficiency and flexibility when, for instance, the bulkier items are less frequently found in the general item population.